POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x
Leverage a lightning fast DataFrame library for efficient data wrangling in Python Key Features Unlock the power of Python Polars for faster and more efficient data analysis workflows Master the fundamentals of Python Polars with step-by-step recipes Discover data manipulation techniques to apply ac...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing Ltd.
2024
|
| Ausgabe: | 1st edition. |
| Schlagworte: | |
| Online-Zugang: | lizenzpflichtig |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
MARC
| LEADER | 00000nam a22000002 4500 | ||
|---|---|---|---|
| 001 | ZDB-30-ORH-108527433 | ||
| 003 | DE-627-1 | ||
| 005 | 20241001123226.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 241001s2024 xx |||||o 00| ||eng c | ||
| 020 | |a 9781805125150 |c electronic bk. |9 978-1-80512-515-0 | ||
| 020 | |a 180512515X |c electronic bk. |9 1-80512-515-X | ||
| 020 | |a 9781805121152 |9 978-1-80512-115-2 | ||
| 035 | |a (DE-627-1)108527433 | ||
| 035 | |a (DE-599)KEP108527433 | ||
| 035 | |a (ORHE)9781805121152 | ||
| 035 | |a (DE-627-1)108527433 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 082 | 0 | |a 005.7 |2 23/eng/20240903 | |
| 100 | 1 | |a Kakegawa, Yuki |e VerfasserIn |4 aut | |
| 245 | 1 | 0 | |a POLARS COOKBOOK |b over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x |c Yuki Kakegawa |
| 250 | |a 1st edition. | ||
| 264 | 1 | |a Birmingham, UK |b Packt Publishing Ltd. |c 2024 | |
| 300 | |a 1 online resource | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Leverage a lightning fast DataFrame library for efficient data wrangling in Python Key Features Unlock the power of Python Polars for faster and more efficient data analysis workflows Master the fundamentals of Python Polars with step-by-step recipes Discover data manipulation techniques to apply across multiple data problems Purchase of the print or Kindle book includes a free PDF eBook Book Description Polars Cookbook is a complete guide that not only helps you get started with Python Polars but also gives you effective solutions to your day-to-day data problems. Dive into the world of Polars, a high-performance DataFrame library designed for efficient data processing and analysis. This cookbook takes a practical approach to unlocking the full potential of Polars through detailed, step-by-step recipes. Starting with installation and basic operations, this book guides you through data manipulation, advanced querying, and performance optimization techniques. You'll learn how to handle large datasets, perform complex transformations, and leverage Polars' powerful features for data science tasks. As you progress, you'll explore Polars' integration with other tools and libraries, and discover how to deploy Polars in both onpremises and cloud environments. You'll also explore use cases for data engineering, time series analysis, statistical analysis, and machine learning, providing essential strategies for securing and optimizing your Polars workflows. By the end of this book, you'll have acquired the knowledge and skills to build scalable, efficient, and reliable data processing solutions using Polars. What you will learn Read from different data sources and write to various files and databases Apply aggregations, window functions, and string manipulations Perform common data tasks such as handling missing values and performing list and array operations Discover how to reshape and tidy your data by pivoting, joining, and concatenating Analyze your time series data in Python Polars Create better workflows with testing and debugging Who this book is for This book is for data analysts, data scientists, and data engineers who want to learn how to use Polars in their workflows. Working knowledge of the Python programming language is required. Experience working with a DataFrame library such as pandas or PySpark will also be helpful. | ||
| 650 | 0 | |a Big data | |
| 650 | 0 | |a Data mining | |
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 4 | |a Exploration de données (Informatique) | |
| 650 | 4 | |a Python (Langage de programmation) | |
| 776 | 1 | |z 1805121154 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 1805121154 |
| 856 | 4 | 0 | |l TUM01 |p ZDB-30-ORH |q TUM_PDA_ORH |u https://learning.oreilly.com/library/view/-/9781805121152/?ar |m X:ORHE |x Aggregator |z lizenzpflichtig |3 Volltext |
| 912 | |a ZDB-30-ORH | ||
| 951 | |a BO | ||
| 912 | |a ZDB-30-ORH | ||
| 049 | |a DE-91 | ||
Datensatz im Suchindex
| DE-BY-TUM_katkey | ZDB-30-ORH-108527433 |
|---|---|
| _version_ | 1818767363615490048 |
| adam_text | |
| any_adam_object | |
| author | Kakegawa, Yuki |
| author_facet | Kakegawa, Yuki |
| author_role | aut |
| author_sort | Kakegawa, Yuki |
| author_variant | y k yk |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-30-ORH |
| ctrlnum | (DE-627-1)108527433 (DE-599)KEP108527433 (ORHE)9781805121152 |
| dewey-full | 005.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.7 |
| dewey-search | 005.7 |
| dewey-sort | 15.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 1st edition. |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03887nam a22004332 4500</leader><controlfield tag="001">ZDB-30-ORH-108527433</controlfield><controlfield tag="003">DE-627-1</controlfield><controlfield tag="005">20241001123226.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">241001s2024 xx |||||o 00| ||eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781805125150</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">978-1-80512-515-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">180512515X</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">1-80512-515-X</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781805121152</subfield><subfield code="9">978-1-80512-115-2</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)108527433</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP108527433</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ORHE)9781805121152</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627-1)108527433</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">005.7</subfield><subfield code="2">23/eng/20240903</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kakegawa, Yuki</subfield><subfield code="e">VerfasserIn</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">POLARS COOKBOOK</subfield><subfield code="b">over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x</subfield><subfield code="c">Yuki Kakegawa</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK</subfield><subfield code="b">Packt Publishing Ltd.</subfield><subfield code="c">2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Leverage a lightning fast DataFrame library for efficient data wrangling in Python Key Features Unlock the power of Python Polars for faster and more efficient data analysis workflows Master the fundamentals of Python Polars with step-by-step recipes Discover data manipulation techniques to apply across multiple data problems Purchase of the print or Kindle book includes a free PDF eBook Book Description Polars Cookbook is a complete guide that not only helps you get started with Python Polars but also gives you effective solutions to your day-to-day data problems. Dive into the world of Polars, a high-performance DataFrame library designed for efficient data processing and analysis. This cookbook takes a practical approach to unlocking the full potential of Polars through detailed, step-by-step recipes. Starting with installation and basic operations, this book guides you through data manipulation, advanced querying, and performance optimization techniques. You'll learn how to handle large datasets, perform complex transformations, and leverage Polars' powerful features for data science tasks. As you progress, you'll explore Polars' integration with other tools and libraries, and discover how to deploy Polars in both onpremises and cloud environments. You'll also explore use cases for data engineering, time series analysis, statistical analysis, and machine learning, providing essential strategies for securing and optimizing your Polars workflows. By the end of this book, you'll have acquired the knowledge and skills to build scalable, efficient, and reliable data processing solutions using Polars. What you will learn Read from different data sources and write to various files and databases Apply aggregations, window functions, and string manipulations Perform common data tasks such as handling missing values and performing list and array operations Discover how to reshape and tidy your data by pivoting, joining, and concatenating Analyze your time series data in Python Polars Create better workflows with testing and debugging Who this book is for This book is for data analysts, data scientists, and data engineers who want to learn how to use Polars in their workflows. Working knowledge of the Python programming language is required. Experience working with a DataFrame library such as pandas or PySpark will also be helpful.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Big data</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Exploration de données (Informatique)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python (Langage de programmation)</subfield></datafield><datafield tag="776" ind1="1" ind2=" "><subfield code="z">1805121154</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">1805121154</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">TUM01</subfield><subfield code="p">ZDB-30-ORH</subfield><subfield code="q">TUM_PDA_ORH</subfield><subfield code="u">https://learning.oreilly.com/library/view/-/9781805121152/?ar</subfield><subfield code="m">X:ORHE</subfield><subfield code="x">Aggregator</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">BO</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-ORH</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-30-ORH-108527433 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-18T08:48:42Z |
| institution | BVB |
| isbn | 9781805125150 180512515X 9781805121152 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 online resource |
| psigel | ZDB-30-ORH |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | Packt Publishing Ltd. |
| record_format | marc |
| spelling | Kakegawa, Yuki VerfasserIn aut POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x Yuki Kakegawa 1st edition. Birmingham, UK Packt Publishing Ltd. 2024 1 online resource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Leverage a lightning fast DataFrame library for efficient data wrangling in Python Key Features Unlock the power of Python Polars for faster and more efficient data analysis workflows Master the fundamentals of Python Polars with step-by-step recipes Discover data manipulation techniques to apply across multiple data problems Purchase of the print or Kindle book includes a free PDF eBook Book Description Polars Cookbook is a complete guide that not only helps you get started with Python Polars but also gives you effective solutions to your day-to-day data problems. Dive into the world of Polars, a high-performance DataFrame library designed for efficient data processing and analysis. This cookbook takes a practical approach to unlocking the full potential of Polars through detailed, step-by-step recipes. Starting with installation and basic operations, this book guides you through data manipulation, advanced querying, and performance optimization techniques. You'll learn how to handle large datasets, perform complex transformations, and leverage Polars' powerful features for data science tasks. As you progress, you'll explore Polars' integration with other tools and libraries, and discover how to deploy Polars in both onpremises and cloud environments. You'll also explore use cases for data engineering, time series analysis, statistical analysis, and machine learning, providing essential strategies for securing and optimizing your Polars workflows. By the end of this book, you'll have acquired the knowledge and skills to build scalable, efficient, and reliable data processing solutions using Polars. What you will learn Read from different data sources and write to various files and databases Apply aggregations, window functions, and string manipulations Perform common data tasks such as handling missing values and performing list and array operations Discover how to reshape and tidy your data by pivoting, joining, and concatenating Analyze your time series data in Python Polars Create better workflows with testing and debugging Who this book is for This book is for data analysts, data scientists, and data engineers who want to learn how to use Polars in their workflows. Working knowledge of the Python programming language is required. Experience working with a DataFrame library such as pandas or PySpark will also be helpful. Big data Data mining Python (Computer program language) Exploration de données (Informatique) Python (Langage de programmation) 1805121154 Erscheint auch als Druck-Ausgabe 1805121154 TUM01 ZDB-30-ORH TUM_PDA_ORH https://learning.oreilly.com/library/view/-/9781805121152/?ar X:ORHE Aggregator lizenzpflichtig Volltext |
| spellingShingle | Kakegawa, Yuki POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x Big data Data mining Python (Computer program language) Exploration de données (Informatique) Python (Langage de programmation) |
| title | POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x |
| title_auth | POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x |
| title_exact_search | POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x |
| title_full | POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x Yuki Kakegawa |
| title_fullStr | POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x Yuki Kakegawa |
| title_full_unstemmed | POLARS COOKBOOK over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x Yuki Kakegawa |
| title_short | POLARS COOKBOOK |
| title_sort | polars cookbook over 60 practical recipes to transform manipulate and analyze your data using python polars 1 x |
| title_sub | over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x |
| topic | Big data Data mining Python (Computer program language) Exploration de données (Informatique) Python (Langage de programmation) |
| topic_facet | Big data Data mining Python (Computer program language) Exploration de données (Informatique) Python (Langage de programmation) |
| url | https://learning.oreilly.com/library/view/-/9781805121152/?ar |
| work_keys_str_mv | AT kakegawayuki polarscookbookover60practicalrecipestotransformmanipulateandanalyzeyourdatausingpythonpolars1x |